ArticleSAGE open medicine2026
Screening of key genes in infectious ARDS and development of a disease risk prediction model.
Article in SAGE open medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infection-associated acute respiratory distress syndrome (ARDS) is a common and severe clinical disease in critical care medicine, with high mortality and a significant burden on intensive care resources. Current treatments mainly rely on supportive care, and there is still a lack of effective targeted drugs and diagnostic tools. Therefore, in-depth exploration of its molecular mechanisms and identification of key genes have important clinical significance. Objective: To screen infectious ARDS key genes, construct a risk prediction model, and explore targeted drugs. Methods: We extracted GSE32707 data from the GEO database, analyzed infection-related ARDS samples and control samples, screened for differentially expressed genes, and identified signaling pathways using GO and KEGG methods. Core genes were subsequently selected for molecular docking using HadDOCK. Notably, this study integrates multiple analytical approaches, including differentially expressed gene analysis, pathway enrichment, ceRNA network construction, immune infiltration characterization, and molecular docking into a systematic framework, which to our knowledge has not been previously applied to infectious ARDS in a coordinated manner. By integrating ceRNA networks to reveal immune characteristics, we validated key gene expressions and predicted targeted therapies. Results: In patients with infectious ARDS, 3,034 differentially expressed genes were identified, enriched in T cell receptors, autophagy, and the PI3K/Akt/mTOR signaling pathway. Network analysis pinpointed key genes including ATG5, AKT1, ATG7, and BMP9, with ATG5 strongly associated with CD4 Conclusion: BMP9, AKT1, ATG5, and ATG7 may contribute to ARDS pathogenesis through immune cell infiltration and signaling pathway regulation. The risk model and sorafenib-targeted strategy provide preliminary insights and new directions for clinical diagnosis and treatment though further validation is needed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.